Device control method, apparatus, equipment, medium and product based on user habits

Abstract

The present invention relates to the field of device control technology, and discloses a device control method, apparatus, equipment, medium and product based on user habits. The present invention determines the local time of the environment in which the device is located through light intensity change data, and calibrates the device clock. The calibrated device clock is then used to record the user's device usage within a preset period, and by identifying the working days and rest days within the preset period, the user's usage habits on working days and rest days are learned. Therefore, during the operation of the device, the device can be controlled in combination with the user's usage habits that match the current date. The present application can also automatically reset the local time of the device in the absence of a network connection and in an environment across time zones, thereby recording and learning user habits that are consistent with the user's local time according to the local time, preventing the habits set by the device from being inconsistent with the user's real habits, and improving the user's device usage experience.

Description

Technical Field

[0001] The present invention relates to the field of device control technology, and in particular to a method, apparatus, device, medium and product for device control based on user habits. Background Art

[0002] Device timing can provide a precise time reference for automated device control and is a key technology for implementing functions such as device timing control, event marking, and collaborative synchronization.

[0003] Conventional home appliances require an internet connection to record data, and they need to be constantly running to maintain this connection. This can lead to bandwidth usage and affect network speed and stability. Conventional devices generally record data based on Beijing time, and users often set their schedules based on Beijing time. However, the actual local time in some countries, regions, or remote provinces in China does not correspond to Beijing time. For example, at 8:00 Beijing time, some areas are already at noon. This can cause the device's schedule to be inconsistent with the user's local schedule and actual habits, impacting the user experience. Summary of the Invention

[0004] In view of this, the present invention provides a device control method, apparatus, device, medium and product based on user habits to solve the problem that conventional devices cannot set user habits according to the user's actual local time, which easily affects the user experience.

[0005] In a first aspect, the present invention provides a device control method based on user habits, the method comprising:

[0006] Based on the light intensity change data of the device's environment, the local time of the device's environment is determined, and the device clock is calibrated based on the local time;

[0007] Using the calibrated device clock, monitor the user's device usage within a preset period; wherein the preset period includes multiple consecutive days;

[0008] Based on device usage, identify working days and weekends within a preset period, and determine the user's usage habits on working days and weekends respectively;

[0009] The current date is determined using a calibrated device clock, and the device is controlled according to a user usage habit that matches the current date; wherein the current date is a working day or a rest day.

[0010] This application uses light intensity change data to determine the local time of the device's environment and calibrate the device clock. The calibrated device clock is then used to record the user's device usage within a preset period, and by identifying the working days and rest days within the preset period, the user's usage habits on working days and rest days are learned. Therefore, during device operation, the device can be controlled in combination with the user's usage habits that match the current date. This application can automatically reset the local time of the device even when there is no network connection and the environment spans time zones, thereby recording and learning user habits that are consistent with the user's local time according to the local time, preventing the device-set habits from being inconsistent with the user's real habits, and improving the user's device usage experience.

[0011] In an optional embodiment, monitoring the user's device usage within a preset period using a calibrated device clock includes:

[0012] For each time period of each day within a preset period, determining the device usage status corresponding to the time period; wherein each day includes multiple time periods, the time periods are determined based on a calibrated device clock, and the device usage status includes being used and not being used;

[0013] According to the device usage status corresponding to multiple time periods of each day, the user's device usage status within a preset period is obtained.

[0014] This application uses a calibrated device clock to monitor the user's device usage status in multiple time periods every day, and obtains the user's device usage within a preset period, so that the recorded user habits are consistent with the local time.

[0015] In an optional embodiment, controlling the device according to the user's usage habits that match the current date includes:

[0016] Determine a target time period during which the user's device usage status on the current date is unused based on the user's usage habits that match the current date;

[0017] The target function of the control device stops running during the target time period.

[0018] This application controls the target functions of the entire device to stop running during the target time period, that is, when the user is not using the device, to save energy and avoid performance degradation and life reduction caused by long-term operation of components.

[0019] In an optional embodiment, identifying working days and rest days within a preset period based on device usage includes:

[0020] Based on the device usage, determine a first time period and a second time period on the first day of a preset period, and determine the total time of use of the first device on the first day; wherein the first time period is a time period when the device is in use, and the second time period is a time period when the device is not in use;

[0021] For each day of the preset period except the first day, based on device usage, determine the number of non-habitual time periods on that day and determine the total second device usage time on that day; wherein the non-habitual time periods include a time period corresponding to the first time period on the first day and in which the device is not in use, and a time period corresponding to the second time period on the first day and in which the device is in use;

[0022] Based on the relationship between the total usage time of the first device, the total usage time of the second device, and the number of non-habitual time periods and a preset number, working days and rest days within the preset period are identified.

[0023] The present application determines the first time period of device use, the second time period of device non-use, and the total time of use of the first device on the first day of a preset period, and then obtains the number of non-habitual time periods and the total time of use of the second device for each day except the first day based on the first time period and the second time period. In order to identify the working days and rest days in the preset period based on the relationship between the number of non-habitual time periods and the preset number and the comparison between the total time of use of the first device and the total time of use of the second device, thereby recording and learning the user's usage habits on weekdays and rest days respectively.

[0024] In an optional embodiment, identifying working days and rest days within a preset period based on a relationship between the total usage time of the first device, the total usage time of the second device, and the number of non-habitual time periods and a preset number includes:

[0025] For each day other than the first day within the preset period, if the number of non-habitual time periods of the user on that day is greater than a preset threshold, and the difference between the total usage time of the second device and the total usage time of the first device is not greater than a preset difference, then the day is determined to be a working day;

[0026] For each day except the first day within the preset period, if the number of non-habitual time periods of the user on that day is greater than the preset number threshold, and the difference between the total usage time of the second device and the total usage time of the first device is greater than the preset difference, then that day will be determined as a rest day.

[0027] This application identifies the working days and rest days of a preset cycle based on the number of non-habitual time periods of the user compared to the first day each day within the preset cycle and the total device usage time, so as to record and learn the user's usage habits on weekdays and rest days respectively.

[0028] In an optional embodiment, determining the local time of the environment in which the device is located based on light intensity change data of the environment in which the device is located includes:

[0029] Determine, based on the light intensity variation data of the environment in which the device is located, a first moment and a second moment at which the light intensity decreases from a maximum value for two consecutive times;

[0030] Determine the morning end time based on the first time and the second time;

[0031] The local time of the device's environment is determined by clocking in based on the end of the morning.

[0032] This application uses data on light intensity changes in the device's environment to identify the times when light intensity decreases from its maximum value twice in a row. It then uses the symmetry of morning and afternoon to calculate the end of morning and midnight local time, thereby timing based on midnight and determining the local time of the device's environment. This allows the device's local time to be automatically reset even when there's no network connection or when the environment spans multiple time zones. This allows the device to record and learn user habits based on local time, better aligning with the local user's schedule.

[0033] In an optional embodiment, the method further includes:

[0034] Receive custom habit data input by the user;

[0035] Based on customized habit data, user usage habits are corrected.

[0036] This application allows users to input custom habit data, and the device corrects the user's usage habits based on the custom habit data, so that the corrected user usage habits can balance user needs and self-learned user usage habits, thereby improving user experience.

[0037] In a second aspect, the present invention provides a device control apparatus based on user habits, the device comprising:

[0038] A first processing module is configured to determine the local time of the environment in which the device is located based on the light intensity change data of the environment in which the device is located, and calibrate the device clock based on the local time;

[0039] A second processing module is configured to monitor the user's device usage within a preset period using the calibrated device clock; wherein the preset period includes a plurality of consecutive days;

[0040] A third processing module is configured to identify working days and weekends within a preset period based on device usage, and determine the user's usage habits on working days and weekends respectively;

[0041] The fourth processing module is used to determine the current date using the calibrated device clock and control the device according to the user's usage habits that match the current date; wherein the current date is a working day or a holiday.

[0042] In a third aspect, the present invention provides a household appliance comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the device control method based on user habits of the above-mentioned first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0043] In an optional embodiment, the household appliance is an ice maker.

[0044] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the device control method based on user habits of the above-mentioned first aspect or any corresponding embodiment thereof.

[0045] In a fifth aspect, the present invention provides a computer program product comprising computer instructions for causing a computer to execute the device control method based on user habits of the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 is a flowchart of a device control method based on user habits according to an embodiment of the present invention;

[0048] Figure 2 is a flowchart of another device control method based on user habits according to an embodiment of the present invention;

[0049] Figure 3 is a flowchart of another device control method based on user habits according to an embodiment of the present invention;

[0050] Figure 4 is a structural block diagram of a device control apparatus based on user habits according to an embodiment of the present invention;

[0051] Figure 5 Schematic diagram of the hardware structure of the household appliance according to an embodiment of the present invention. DETAILED DESCRIPTION

[0052] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0053] According to an embodiment of the present invention, an embodiment of a device control method based on user habits is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0054] In this embodiment, a device control method based on user habits is provided, which can be used for devices that are controlled based on timing, such as ice makers, etc. Figure 1 is a flow chart of a device control method based on user habits according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0055] Step S101 : determining the local time of the environment where the device is located based on light intensity change data of the environment where the device is located, and calibrating the device clock based on the local time.

[0056] Specifically, a photosensor can be used to collect changes in the scattered light in the device's environment to obtain light intensity change data. It should be noted that the change in scattered light is minimally affected by weather. If the weather is consistent throughout the day—for example, cloudy, overcast, rainy, sunny, or sunny in the morning and rainy in the afternoon—then noon local time will correspond to the maximum scattered light intensity.

[0057] It should be noted that the photosensor can continuously capture changes in scattered light, or capture changes in scattered light at regular intervals, such as 10 minutes. The photosensor can be a photoresistor, a light intensity sensor, etc., and this application is not limited to this.

[0058] In this embodiment, in order to further eliminate factors such as inconsistent light intensity of scattered light from the north and south balconies and asymmetric light intensity in the morning and afternoon, the photosensor can be installed in a place on the equipment that cannot be directly exposed to sunlight but is connected to the scattered light from the external environment. This place can be a downward hole on the equipment or some structures that can block light, such as the equipment's vents, blinds, etc., as long as it can block direct sunlight, this application is not limited to this.

[0059] In step S101, the light intensity change data of the environment in which the device is located is collected through a photosensor, so as to identify the actual local time of the environment in which the device is located, such as the time when the light intensity is minimum at 0 o'clock at night and the time when the light intensity is maximum at 12 o'clock at noon, etc., so as to calibrate the device clock to make the device clock consistent with the local time.

[0060] Step S102: Using the calibrated device clock, monitor the user's device usage within a preset period; wherein the preset period includes multiple consecutive days.

[0061] Specifically, the calibrated device clock is used to identify the user's device usage in various time periods over multiple consecutive days, thereby obtaining the user's device usage over a preset period. It should be noted that the preset period should be a number of consecutive days. The preset period can be a week, half a month, a month, etc., and can be set according to actual scenarios. This application is not limited to this.

[0062] Step S103 , based on the device usage, identifying the working days and weekends within a preset period, and determining the user's usage habits on the working days and weekends respectively.

[0063] Specifically, the distribution of working days and rest days within a preset period is identified based on device usage. Generally speaking, the more the device is used, the more likely it is that the day is a rest day, and the less the device is used, the more likely it is that the day is a working day. The user's usage habits on working days and rest days are determined respectively.

[0064] Taking a preset period of 7 consecutive days as an example, by continuously identifying 7 days, the distribution of complete rest days (indicated by "1") and working days (indicated by "0") in the preset period can be obtained. The distribution may be 7 different permutations and combinations of 1 and 0, such as 0011000, 1100000, 1001111, 1100111, 1111111, 1000000, and 0000000.

[0065] Step S104, using the calibrated device clock to determine the current date, and controlling the device according to the user's usage habits that match the current date; wherein the current date is a working day or a holiday.

[0066] Specifically, the calibrated device clock is used to determine whether the current date is a working day or a holiday, and then the device is controlled using the user's usage habits that match the current date.

[0067] Related technologies fail to consider the consistency between the actual local time and the system time in the device's environment. Furthermore, after a power outage, the device must rely on its internal clock for timing. If an external network interruption, such as a broadband outage, occurs after power is restored, the internal clock cannot be updated in a timely manner, causing errors between the clock timing and the set time. Furthermore, if the power is off for an extended period, maintaining the internal clock requires large-capacity capacitors and components, which is uneconomical and takes up space on the entire device.

[0068] For example, if a user changes their wireless network password but forgets to set up a new Wi-Fi connection for their device, the device will be disconnected for a long time and unable to connect to the network to obtain time. If the user unplugs the device mid-trip, such as for a business trip or out of habit, the battery inside the device may not last long enough, resulting in incorrect time after powering it back on. These situations can cause the device's timekeeping system to fail, resulting in a discrepancy between the actual local time and the device's actual location, leading to errors in device control.

[0069] The device control method based on user habits provided in this embodiment determines the local time of the environment in which the device is located through light intensity change data and calibrates the device clock. The calibrated device clock is then used to record the user's device usage within a preset period, and by identifying the working days and rest days within the preset period, the user's usage habits on working days and rest days are learned. Therefore, during device operation, the device can be controlled in combination with the user's usage habits that match the current date. This application can also automatically reset the local time of the device when there is no network connection and the environment spans time zones, thereby recording and learning user habits that are consistent with the user's local time according to the local time, preventing the habits set by the device from being inconsistent with the user's actual habits, and improving the user's device usage experience.

[0070] In this embodiment, a device control method based on user habits is provided, which can be used for devices that are controlled based on timing, such as ice makers, etc. Figure 2 is a flow chart of a device control method based on user habits according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0071] Step S201 : determining the local time of the environment where the device is located based on the light intensity change data of the environment where the device is located, and calibrating the device clock based on the local time.

[0072] In some optional implementations, the above step S201 includes:

[0073] Step a1: Based on the light intensity variation data of the environment in which the device is located, determine the first moment and the second moment when the light intensity decreases from the maximum light intensity twice in a row.

[0074] Specifically, the light intensity change data is identified to determine the moment when the light intensity starts to decrease from the maximum value for the first time or maintains the maximum value for a period of time and then starts to decrease, that is, the moment when the light intensity I0 collected at the latter moment is less than the light intensity I1 collected at the previous moment, indicating that noon with local 12 o'clock as the midpoint has passed and the start time of the afternoon has arrived. The internal system records the start time of the afternoon as the first moment T0.

[0075] Furthermore, if the light intensity gradually decreases to a minimum value or remains at the minimum value for a period of time before increasing again, it indicates that "night" has passed and the next day has begun. The light intensity continues to increase until the light intensity begins to decrease from the maximum value for the second time or remains at the maximum value for a period of time before beginning to decrease again. This indicates that the afternoon of the next day has begun and this time is recorded as the second time T1.

[0076] In some embodiments, in order to eliminate the influence of weather factors such as cloudy days and rainy days on the light intensity change data, after determining the first moment T0 and the second moment T1, calculate whether the time difference between the first moment T0 and the second moment T1 is 24 hours (error is allowed, such as the error is 10 minutes to 30 minutes). If the time difference is 24 hours within the allowable error, execute step a2; otherwise, it means that abnormal weather conditions have occurred, such as abnormal weather conditions where it is cloudy and rainy in the morning or at noon and suddenly turns sunny in the afternoon. In this case, the first moment T0 and the second moment T1 are collected again until the event difference between the first moment T0 and the second moment T1 is 24 hours within the allowable error.

[0077] It should be noted that if the weather conditions are abnormal, such as the previous day being cloudy and sunny, and the next day being sunny or rainy, the time difference between two consecutive identified afternoon start times cannot be close to 24 hours due to recognition bias. However, if two consecutive days are cloudy all day, overcast, rainy, sunny, or sunny in the morning and rainy in the afternoon, the time difference should be close to 24 hours.

[0078] In related technologies, using photosensors to sense differences in external light and directly determine whether it is day or night is prone to failure, especially when there is weak lighting at night, when the user does not turn on the lights in the evening but the light is dim, and when the user places the device in a relatively dark place. If there are human factors such as light bulbs turning on or flashlights shining, recognition errors may occur.

[0079] In an embodiment of the present invention, in order to avoid recognition errors such as light bulbs turning on and off, flashlights shining, etc., a light intensity mutation processing mechanism is added to eliminate the interference of mutation signals. When the light intensity is detected to increase or decrease rapidly within a set short period of time, and the increase or decrease value is less than the set light intensity allowable change value, a "light intensity mutation situation" is detected. This "light intensity mutation situation" will be resolved when the light intensity returns to a light intensity value similar to that before the mutation. If the moment when the light intensity begins to decrease from the maximum light intensity is detected under the "light intensity mutation situation", then this moment will not be recorded as the first moment T0 and the second moment T1.

[0080] Step a2: determining the end time of the morning based on the first time and the second time.

[0081] Specifically, since the system records local time, morning and afternoon are symmetrical, and the start time of afternoon is the end time of morning. According to T = (24 + T1 - T0) / 2, we can get half of the total time from the start time of afternoon to the end time of the next morning, so the end time of morning can be set to T.

[0082] For example, before calibrating the device clock, the first moment T0 is identified at 2 pm on the first day, and the second moment T1 is identified at 12 am on the second day. Then the interval between them is 24+12-14=22 hours, 22 / 2=11 hours, and the end time of the morning can be identified as 11 o'clock local time, that is, the 12 o'clock in the morning identified before the clock calibration corresponds to 11 o'clock local time.

[0083] Step a3: clocking based on the end time of the morning to determine the local time of the environment where the device is located.

[0084] Specifically, after identifying the end of the morning, T, i.e., the time between midnight and the end of the morning, T, then midnight local time is T1-T. Timekeeping is then started based on a 24-hour day to determine the local time of the device's environment. Using the example of step a2, if 12:00 AM on the clock before calibration corresponds to 11:00 local time, then 1:00 AM on the clock before calibration corresponds to midnight local time. Timekeeping is then restarted based on midnight to determine the local time of the device.

[0085] The embodiment of the present application uses data on light intensity changes in the device's environment to identify the times when light intensity decreases from its maximum value twice in a row. The embodiment then uses the symmetry between morning and afternoon to calculate the end of morning and the local time of midnight. This allows timing based on midnight to determine the local time of the device's environment. This allows the device's local time to be automatically reset even when there's no network connection or when the environment spans multiple time zones. This allows the device to record and learn user habits based on local time, better aligning with the local user's schedule.

[0086] Step S202: Using the calibrated device clock, monitor the user's device usage within a preset period; wherein the preset period includes multiple consecutive days.

[0087] Specifically, the above step S202 includes:

[0088] Step S2021, for each time period of each day within a preset cycle, determine the device usage status corresponding to the time period; wherein each day includes multiple time periods, the time periods are determined based on the calibrated device clock, and the device usage status includes used and not used.

[0089] Specifically, use the calibrated device clock to identify the local time and divide each day into multiple time periods, such as 0:00-6:00, 6:00-10:00, 10:00-14:00, 14:00-16:00, and 16:00-0:00, corresponding to five time periods with different demands: evening rest, morning, midday, afternoon, and night. Alternatively, divide the day directly into 24 segments based on a 24-hour period (if this is done, the local midnight time can be omitted).

[0090] In some embodiments, whether the user uses the device in each time period is monitored. If used, the device usage status corresponding to the time period is determined to be used; if the user does not use the device in the time period, the device usage status corresponding to the time period is determined to be not used.

[0091] In other embodiments, whether the user uses the device is monitored in each time period. If used, the earliest usage time and the latest usage time are recorded. If the earliest usage time is less than 30 minutes away from the lower limit of the time period or the latest usage time is less than 30 minutes away from the upper limit of the time period, the entire time period is marked as "user's frequently used time"; otherwise, if within the time period, the user's earliest usage time is pushed forward 30 minutes to the latest usage time and pushed back 30 minutes as "user's frequently used time", and the rest is marked as "user's infrequently used time", so as to obtain the device usage status corresponding to the time period.

[0092] Step S2022: Obtain the device usage status of the user within a preset period based on the device usage status corresponding to multiple time periods each day.

[0093] Specifically, the device usage of the user in the preset period is obtained based on multiple sections of “user frequently used time” and “user infrequently used time” recorded every day in the preset period.

[0094] The embodiment of the present application utilizes a calibrated device clock to monitor the user's device usage status in multiple time periods each day, and obtains the user's device usage within a preset period, so that the recorded user habits are consistent with the local time.

[0095] Step S203 : Based on the device usage, identify the working days and weekends within a preset period, and determine the user's usage habits on the working days and weekends respectively.

[0096] Specifically, the above step S203 includes:

[0097] Step S2031, based on the device usage, determine the first time period and the second time period on the first day of the preset cycle, and determine the total time of use of the first device on the first day; wherein the first time period is the time period when the device usage status is in use, and the second time period is the time period when the device usage status is not in use.

[0098] Specifically, based on the device usage, the user's usage habits on the first day within a preset period are determined. The user usage habits can be composed of multiple first time periods when the device usage status is in use and second time periods when the device usage status is not in use. By summing up the time of all first time periods, the total time of first device usage on the first day is obtained.

[0099] Step S2032, for each day except the first day within the preset period, based on the device usage, determine the number of non-habitual time periods of the day, and determine the total time of second device usage on the day; wherein the non-habitual time periods include the time period corresponding to the first time period of the first day and the device usage status is unused, and the time period corresponding to the second time period of the first day and the device usage status is used.

[0100] Specifically, based on the first day, the user's usage habits for multiple days are continuously identified, and the user's non-habitual time periods are recorded on each day except the first day. The non-habitual time periods include the time periods in which the user does not use or does not use the device for a long time in the time period corresponding to the first time period of the first day (that is, the user has no operation during this time period), and the time period in which the user uses or uses the device for a long time in the time period corresponding to the second time period of the first day (that is, the user has operation during this time period), and the number of non-habitual time periods corresponding to each day and the total usage time of the second device are determined.

[0101] It should be noted that, taking the first time period of the first day as 10:00-14:00 and the second time period of the first day as 16:00-0:00 as an example, the time period of the second day corresponding to the first time period of the first day is 10:00-14:00 of the second day, and the time period of the second day corresponding to the second time period of the first day is 16:00-0:00 of the second day.

[0102] Step S2033: identifying working days and rest days within a preset period based on the relationship between the total usage time of the first device, the total usage time of the second device, and the number of non-habitual time periods and a preset number.

[0103] In some optional implementations, the above step S2033 includes:

[0104] Step b1: For each day except the first day within the preset period, if the number of non-habitual time periods of the user on that day is greater than the preset number threshold, and the difference between the total usage time of the second device and the total usage time of the first device is not greater than the preset difference, then the day is determined to be a working day.

[0105] Step b2: For each day except the first day within the preset period, if the number of non-habitual time periods of the user on that day is greater than the preset number threshold, and the difference between the total usage time of the second device and the total usage time of the first device is greater than the preset difference, then the day is determined as a rest day.

[0106] It should be noted that the preset quantity threshold and the preset difference can be set in combination with specific scenarios.

[0107] In some embodiments, on each day except the first day within a preset cycle, if the number of non-habitual time periods on that day is greater than a preset number threshold, the total time the second device is used on that day is compared with the total time the first device is used. If the total time the second device is used exceeds the total time the first device is used by a large margin, the day is set as a rest day; otherwise, the day is set as a working day.

[0108] In some embodiments, the distribution of working days and rest days is identified multiple times with every 7 days as a preset period to calibrate parameters and ensure the accuracy of the identification of working days and rest days.

[0109] An embodiment of the present application identifies the working days and rest days of a preset cycle based on the number of non-habitual time periods of the user compared to the first day each day within the preset cycle and the total device usage time, so as to record and learn the user's usage habits on weekdays and rest days respectively.

[0110] In an embodiment of the present application, by determining the first time period of device use, the second time period of device non-use, and the total time of use of the first device on the first day of a preset period, the number of non-habitual time periods and the total time of use of the second device on each day except the first day are obtained based on the first time period and the second time period. In this way, based on the relationship between the number of non-habitual time periods and the preset number and the comparison between the total time of use of the first device and the total time of use of the second device, the working days and rest days in the preset period are identified, thereby recording and learning the user's usage habits on weekdays and rest days respectively.

[0111] Step S2034: determining the user's usage habits on weekdays and weekends.

[0112] Specifically, the device usage of the user on weekdays and weekends is identified, and the user usage habits on weekdays and weekends are obtained. The user usage habits include the time periods when the user needs to use the device on weekdays and weekends and the time periods when the user does not need to use the device.

[0113] In some embodiments, user-defined habit data input is received, and the user's usage habits are modified based on the user-defined habit data.

[0114] Specifically, the user's customized habit data can be received through APP and other channels. The customized habit data may include the time periods set by the user for weekdays and weekends when the device needs to be used and when the device does not need to be used. The time periods set by the user can intersect with the time periods of the user's usage habits obtained by self-learning of the device, and the user's usage habits can be corrected using the formed intersection.

[0115] The embodiment of the present application allows the user to input customized habit data, and the device corrects the user's usage habits based on the customized habit data, so that the corrected user usage habits can balance the user's needs and the user usage habits obtained through self-learning, thereby improving the user experience.

[0116] Step S204, using the calibrated device clock to determine the current date, and controlling the device according to the user's usage habits that match the current date; wherein the current date is a working day or a holiday.

[0117] Specifically, the above step S204 includes:

[0118] Step S2041 , determining the current date using the calibrated device clock, and determining a target time period in which the user's device usage status on the current date is unused based on the user's usage habits that match the current date.

[0119] Specifically, the calibrated device clock is used to determine whether the current date is a weekday or a holiday. If it is a weekday, the user usage habits that match the weekday are used to determine the target time period in the current date when the device does not need to be used; if it is a holiday, the user usage habits that match the holiday are used to determine the target time period in the current date when the device does not need to be used.

[0120] Step S2042: Control the target function of the device to stop running during the target time period.

[0121] Specifically, during the target time period, that is, when the user is not using the device, all or part of the functions of the entire device are controlled to stop, thereby entering energy-saving mode to save energy and avoid performance degradation and life reduction caused by long-term operation of components.

[0122] In some embodiments, an interrupt mode of the energy-saving mode can be set so that when the user uses the device during non-customary time periods, the device can quickly respond to user needs and return to normal mode.

[0123] The following describes in detail the device control based on user habits of the present invention with reference to a specific application example. Figure 3 As shown, this application example includes the following steps:

[0124] In step S1, a light-sensitive sensor or a light-sensitive resistor is used to capture the signals of "end of morning" and "start of afternoon", and the local actual night time 24:00 (also called 0:00) is first identified.

[0125] Specifically, in order to avoid recognition errors (such as when a light bulb is turned on or a flashlight is shone), a light intensity mutation processing mechanism is added to eliminate the interference of mutation signals.

[0126] Step S2: Divide the time of the day into multiple groups, and monitor whether the user uses the device in each group of time. If the user uses the device, record the earliest usage time and the latest usage time. If the usage time is less than a certain number of minutes (for example, 30 minutes) from the upper or lower limit of the segmented time, mark the entire time as "user's frequently used time"; otherwise, within this period, push the earliest usage time forward by a certain number of minutes and push the latest usage time backward by a certain number of minutes as "user's frequently used time", and mark the rest as "user's infrequently used time".

[0127] Step S3: Obtaining the user's usage habits in different time periods of the day, such as morning, noon, and evening.

[0128] Step S4, continuously identifying seven days, judging and recording the distribution of working days and rest days and the differences in usage habits, and finally obtaining the complete user usage habits.

[0129] Step S5: When the user is not using the device, all or part of the device is disabled to save energy and reduce the performance degradation and lifespan of components caused by long-term operation. It is also determined whether it is a weekday or a weekend, and user habits are adjusted accordingly.

[0130] Specifically, an interruption mode can be set so that when a user uses the device at an unaccustomed time, the device can respond quickly and return to normal mode.

[0131] Step S6: Re-identify the distribution of working days and rest days every 7 days to calibrate the parameters.

[0132] This application targets conventional household appliances. By identifying the local time, the application self-learns the user's usage habits based on the local time, so that the self-learned user usage habits are more in line with the local schedule, so that the user habits learned by the device are consistent with the user's real habits.

[0133] In this embodiment, a device control apparatus based on user habits is also provided. The device is used to implement the above-mentioned embodiments and preferred embodiments. The details that have been described will not be repeated here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

[0134] This embodiment provides a device control device based on user habits, such as Figure 4 Shown, including:

[0135] The first processing module 401 is configured to determine the local time of the device's environment based on the light intensity change data of the device's environment, and calibrate the device clock based on the local time;

[0136] The second processing module 402 is configured to monitor the user's device usage within a preset period using the calibrated device clock; wherein the preset period includes a plurality of consecutive days;

[0137] The third processing module 403 is used to identify working days and weekends within a preset period based on device usage, and determine the user's usage habits on working days and weekends respectively;

[0138] The fourth processing module 404 is configured to determine the current date using the calibrated device clock and control the device according to the user's usage habits that match the current date; wherein the current date is a working day or a holiday.

[0139] In some optional implementations, the first processing module 401 is further configured to:

[0140] Determine, based on the light intensity variation data of the environment in which the device is located, a first moment and a second moment at which the light intensity decreases from a maximum value for two consecutive times;

[0141] Determine the morning end time based on the first time and the second time;

[0142] The local time of the device's environment is determined by clocking in based on the end of the morning.

[0143] In some optional implementations, the second processing module 402 is further configured to:

[0144] For each time period of each day within a preset period, determining the device usage status corresponding to the time period; wherein each day includes multiple time periods, the time periods are determined based on a calibrated device clock, and the device usage status includes being used and not being used;

[0145] According to the device usage status corresponding to multiple time periods of each day, the user's device usage status within a preset period is obtained.

[0146] In some optional implementations, the third processing module 403 is further configured to:

[0147] Based on the device usage, determine a first time period and a second time period on the first day of a preset period, and determine the total time of use of the first device on the first day; wherein the first time period is a time period when the device is in use, and the second time period is a time period when the device is not in use;

[0148] For each day of the preset period except the first day, based on device usage, determine the number of non-habitual time periods on that day and determine the total second device usage time on that day; wherein the non-habitual time periods include a time period corresponding to the first time period on the first day and in which the device is not in use, and a time period corresponding to the second time period on the first day and in which the device is in use;

[0149] Based on the relationship between the total usage time of the first device, the total usage time of the second device, and the number of non-habitual time periods and a preset number, working days and rest days within the preset period are identified.

[0150] In some optional implementations, the third processing module 403 is further configured to:

[0151] For each day other than the first day within the preset period, if the number of non-habitual time periods of the user on that day is greater than a preset threshold, and the difference between the total usage time of the second device and the total usage time of the first device is not greater than a preset difference, then the day is determined to be a working day;

[0152] For each day except the first day within the preset period, if the number of non-habitual time periods of the user on that day is greater than the preset number threshold, and the difference between the total usage time of the second device and the total usage time of the first device is greater than the preset difference, then that day will be determined as a rest day.

[0153] In some optional implementations, the third processing module 403 is further configured to:

[0154] Receive custom habit data input by the user;

[0155] Based on customized habit data, user usage habits are corrected.

[0156] In some optional implementations, the fourth processing module 404 is further configured to:

[0157] Determine a target time period during which the user's device usage status on the current date is unused based on the user's usage habits that match the current date;

[0158] The target function of the control device stops running during the target time period.

[0159] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0160] The device control device based on user habits in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0161] The embodiment of the present invention also provides a household appliance having the above Figure 4 The device control device based on user habits is shown. For example, the home appliance can be an ice maker or other home appliance.

[0162] See also Figure 5 , Figure 5 This is a schematic structural diagram of a household appliance provided by an optional embodiment of the present invention. Figure 5As shown, the household appliance includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the household appliance, including instructions stored in or on the memory to display graphical information of a GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 5 A processor 10 is taken as an example.

[0163] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0164] The memory 20 stores instructions that can be executed by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0165] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the home appliance, etc. In addition, the memory 20 may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the home appliance via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0166] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0167] The home appliance further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 can be connected via a bus or other means. Figure 5 The bus connection is taken as an example.

[0168] The input device 30 can receive input digital or character information and generate key input signals related to user settings and function control of the household appliance. Examples include a touch screen, keypad, mouse, trackpad, touchpad, pointer, one or more mouse buttons, trackball, joystick, etc. The output device 40 may include a display device, auxiliary lighting devices (e.g., LEDs), and tactile feedback devices (e.g., vibration motors). Such display devices include, but are not limited to, liquid crystal displays, light-emitting diodes, monitors, and plasma displays. In some optional embodiments, the display device may be a touch screen.

[0169] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0170] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0171] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A device control method based on user habits, characterized in that: The method comprises: Determining the local time of the environment in which the device is located based on the light intensity change data of the environment in which the device is located, and calibrating the device clock based on the local time; Using the calibrated device clock, monitoring the user's device usage within a preset period; wherein the preset period includes multiple consecutive days; Based on the device usage, identifying working days and rest days within the preset period, and determining the user's usage habits on working days and rest days respectively; The current date is determined using the calibrated device clock, and the device is controlled according to the user's usage habits that match the current date; wherein the current date is a working day or a rest day.

2. The method according to claim 1, characterized in that The method of using the calibrated device clock to monitor the user's device usage within a preset period includes: For each time period of each day within the preset period, determining a device usage status corresponding to the time period; wherein each day includes multiple time periods, the time periods are determined based on a calibrated device clock, and the device usage status includes being used and not being used; According to the device usage status corresponding to multiple time periods of each day, the user's device usage status within a preset period is obtained.

3. The method according to claim 2, characterized in that The controlling of the device according to the user usage habits matching the current date includes: Determining a target time period during which the user's device usage status on the current date is unused based on the user's usage habits that match the current date; The target function of the control device stops running during the target time period.

4. The method according to claim 2, characterized in that The identifying of working days and rest days within the preset period based on the device usage includes: Based on the device usage, determining a first time period and a second time period on the first day of the preset period, and determining the total time of first device usage on the first day; wherein the first time period is a time period when the device is in use, and the second time period is a time period when the device is not in use; For each day of the preset period except the first day, determining the number of non-habitual time periods on that day based on the device usage, and determining the total second device usage time on that day; wherein the non-habitual time periods include a time period on that day corresponding to the first time period on the first day and in which the device is in an unused state, and a time period on that day corresponding to the second time period on the first day and in which the device is in an used state; Based on the total usage time of the first device, the total usage time of the second device, and the relationship between the number of non-habitual time periods and a preset number, working days and rest days within a preset period are identified.

5. The method according to claim 4, characterized in that The identifying of working days and rest days within a preset period based on a relationship between the total usage time of the first device, the total usage time of the second device, and the number of non-habitual time periods and a preset number includes: For each day other than the first day within the preset period, if the number of the user's non-habitual time periods on that day is greater than a preset threshold, and the difference between the total usage time of the second device and the total usage time of the first device is not greater than a preset difference, then the day is determined to be a working day; For each day except the first day within the preset period, if the number of non-habitual time periods of the user on that day is greater than the preset number threshold, and the difference between the total usage time of the second device and the total usage time of the first device is greater than the preset difference, then that day will be determined as a rest day.

6. The method according to any one of claims 1 to 5, characterized in that The determining of the local time of the environment in which the device is located based on the light intensity change data of the environment in which the device is located includes: Determine, based on the light intensity variation data of the environment in which the device is located, a first moment and a second moment at which the light intensity decreases from a maximum value for two consecutive times; Determine the morning end time based on the first time and the second time; The local time of the environment where the device is located is determined by performing clock timing based on the end time of the morning.

7. The method according to any one of claims 1 to 5, characterized in that The method further comprises: Receive custom habit data input by the user; Based on the customized habit data, the user's usage habits are modified.

8. A device control device based on user habits, characterized in that: The device comprises: A first processing module is configured to determine the local time of the environment in which the device is located based on the light intensity change data of the environment in which the device is located, and calibrate the device clock based on the local time; A second processing module is configured to monitor the user's device usage within a preset period using the calibrated device clock; wherein the preset period includes a plurality of consecutive days; A third processing module is configured to identify working days and weekends within the preset period based on the device usage, and determine the user's usage habits on working days and weekends respectively; The fourth processing module is used to determine the current date using the calibrated device clock and control the device according to the user's usage habits that match the current date; wherein the current date is a working day or a holiday.

9. A household appliance, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the device control method based on user habits according to any one of claims 1 to 7 by executing the computer instructions.

10. The household appliance according to claim 9, characterized in that: The household appliance is an ice maker.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the device control method based on user habits according to any one of claims 1 to 7.

12. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the device control method based on user habits according to any one of claims 1 to 7.

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